Psychology Department, Connecticut College, 270 Mohegan Avenue, New London, CT, 06320, USA.
University of Utah, Salt Lake City, USA.
Cogn Res Princ Implic. 2024 Aug 26;9(1):54. doi: 10.1186/s41235-024-00587-1.
Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.
不相关的显著干扰物会触发视觉搜索中的早期放弃，导致观察者错过他们原本可能找到的目标。在这里，我们想知道在那些线索未能突出目标的部分试验中，任务相关的显著线索是否会产生类似的早期放弃效应。我们向参与者呈现了一项困难的视觉搜索任务，并使用了两种提示条件。在高预测条件下，一个以红色圆圈形式呈现的显著线索在大多数有目标出现的情况下突出显示目标。在低预测条件下，线索的准确性要低得多，并且不能可靠地预测目标（即，线索经常是假阳性）。这些与没有呈现线索的对照条件形成对比。在高预测条件下，我们发现了一个明显的证据，即在线索是假阳性的情况下，会出现早期放弃现象，表现在目标不存在的试验中，错误率增加，反应时间缩短。在低预测性线索中，没有观察到这种效应。总的来说，这些结果表明，虚假的显著线索可能会引发早期放弃，尽管可能只有在线索具有高预测价值的情况下才会如此。这些结果对现实世界的搜索有影响，例如医学图像筛查，在这种情况下，显著线索（称为计算机辅助检测或 CAD）可用于突出图像中可能相关的区域，但有时并不准确。
